Compare Azure Databricks and IBM watsonx.data 
Featured Products
At a Glance
Market Segments
Enterprise (48.8% of reviews)
Small-Business (38.1% of reviews)
Entry-Level Pricing
No pricing available
No pricing available
Azure Databricks
Star Rating
(232)4.5 out of 5
Market Segments
Enterprise (48.8% of reviews)
Pros & Cons
Entry-Level Pricing
No pricing available
Learn more about Azure DatabricksIBM watsonx.data
Star Rating
(149)4.4 out of 5
Market Segments
Small-Business (38.1% of reviews)
Pros & Cons
Entry-Level Pricing
No pricing available
Free Trial is available
Learn more about IBM watsonx.dataSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- G2 reviewers report that Azure Databricks excels in ease of use, with users highlighting its ability to simplify large-scale data processing while providing flexibility for engineers. This unified platform allows for seamless data engineering and transformations, making it a favorite among those who prioritize user-friendly applications.
- Users say that IBM watsonx.data stands out for its flexibility in handling various workloads. The ability to run different query engines helps optimize performance and cost, which is particularly beneficial for enterprises that require robust governance features.
- Reviewers mention that Azure Databricks has a strong advantage in real-time analytics, with users appreciating its high performance in data querying. This capability allows teams to execute scripts quickly and efficiently, enhancing productivity in data-heavy tasks.
- According to verified reviews, IBM watsonx.data is praised for its storage optimization and ability to manage large and complex datasets effectively. Users have noted that it performs well in lakehouse-style setups, which is crucial for projects requiring efficient data access and management.
- G2 reviewers report that Azure Databricks offers a smoother implementation process, with many users finding the onboarding experience intuitive. This ease of setup is a significant advantage for teams looking to get started quickly without extensive configuration challenges.
- Users say that while both platforms provide quality support, Azure Databricks has received consistent praise for its quality of support, with users feeling well-supported in their data initiatives. In contrast, IBM watsonx.data's support is seen as adequate but not as highly rated, which may influence user satisfaction in the long run.
Pricing
Entry-Level Pricing
Azure Databricks
No pricing availableIBM watsonx.data
No pricing availableFree Trial
Azure Databricks
No trial information availableIBM watsonx.data
Free Trial is available
Ratings
Meets Requirements
8.9
164
8.8
118
Ease of Use
8.7
165
8.2
132
Ease of Setup
8.6
79
7.9
117
Ease of Admin
8.5
61
7.8
51
Quality of Support
8.5
151
8.5
114
Has the product been a good partner in doing business?
8.8
60
8.7
52
Product Direction (% positive)
9.5
155
9.2
119
Features by Category
Administration
Not enough data
8.0
5
Not enough data
7.0
5
Not enough data
8.0
5
Not enough data
7.7
5
Management
Not enough data
8.3
5
Not enough data
8.3
5
Not enough data
8.0
5
Not enough data
7.7
5
Not enough data
8.3
5
Compliance
Not enough data
8.0
5
Not enough data
7.0
5
Not enough data
7.7
5
Not enough data
7.7
5
Security
Not enough data
8.6
6
Not enough data
9.2
6
Not enough data
8.6
6
Data Quality
Not enough data
8.3
5
Not enough data
8.3
5
Not enough data
8.3
5
Maintainence
Not enough data
8.3
5
Not enough data
8.7
5
Generative AI
Not enough data
Not enough data
Not enough data
Not enough data
Agentic AI - Data Governance
Not enough data
6.0
5
Not enough data
6.0
5
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Management
Not enough data
Not enough data
Not enough data
Not enough data
Functionality
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
System
Not enough data
Not enough data
Model Development
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
8.0
5
Model Development
Not enough data
7.0
5
Machine/Deep Learning Services
Not enough data
Not enough data
Not enough data
7.7
5
Not enough data
Not enough data
Not enough data
Not enough data
Machine/Deep Learning Services
Not enough data
Not enough data
Not enough data
6.7
5
Deployment
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Generative AI
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Agentic AI - Data Science and Machine Learning Platforms
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Data Management
Not enough data
8.3
6
Not enough data
8.6
6
Not enough data
8.3
6
Not enough data
8.3
6
Not enough data
7.5
6
Not enough data
8.1
6
Integration
Not enough data
8.6
6
Not enough data
8.3
6
Not enough data
8.6
6
Deployment
Not enough data
8.1
6
Not enough data
9.4
6
Performance
Not enough data
8.6
6
Security
Not enough data
9.2
6
Not enough data
9.4
6
Generative AI
Not enough data
8.3
5
Not enough data
8.7
5
Data Management
Not enough data
8.2
46
Not enough data
8.5
49
Not enough data
8.5
46
Data as a Service
Not enough data
8.3
46
Not enough data
8.5
47
Architecture
Not enough data
8.3
47
Not enough data
8.5
48
Database
Not enough data
8.6
28
Not enough data
8.8
28
Not enough data
8.6
29
Integrations
Not enough data
8.3
28
Not enough data
8.5
28
Platform
Not enough data
8.4
27
Not enough data
8.6
28
Not enough data
8.5
28
Processing
Not enough data
8.8
27
Not enough data
8.9
25
Data Transformation
8.9
134
|
Verified
7.2
9
9.3
86
|
Verified
7.5
10
Connectivity
8.4
121
|
Verified
7.2
9
9.0
137
|
Verified
7.4
9
9.0
129
|
Verified
8.0
9
9.2
135
|
Verified
7.4
9
Operations
8.3
128
|
Verified
7.5
10
8.6
129
|
Verified
8.0
10
8.5
119
|
Verified
8.2
10
8.5
112
|
Verified
6.8
10
9.3
81
|
Verified
7.8
10
Building Reports
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Platform
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Categories
Categories
Shared Categories
Azure Databricks and IBM watsonx.data are categorized as Big Data Analytics
Unique Categories
Azure Databricks has no unique categories
IBM watsonx.data is categorized as Big Data Processing and Distribution, Data as a Service (DaaS), Data Governance, Data Science and Machine Learning Platforms, Data Warehouse, and ETL Tools
Reviews
Reviewers' Company Size
Azure Databricks
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
IBM watsonx.data
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Small-Business
(50 or fewer emp.)
Mid-Market
(51-1000 emp.)
Enterprise
(> 1000 emp.)
Reviewers' Industry
Information Technology and Services
23.5%
Computer Software
11.8%
Retail
4.9%
Financial Services
4.4%
Automotive
3.9%
Other
51.5%
Information Technology and Services
19.4%
Computer Software
18.7%
Consulting
6.7%
Financial Services
5.2%
Banking
4.5%
Other
45.5%
Alternatives
Discussions
Is Azure Databricks PaaS or SAAS?
2 Comments
PG
Its PaaS tool as it offers developers to build their ETL pipelines for large datasets using multi cluster environment of sparkRead more
What is the best way to databricks in ADF
1 Comment
AS
Firstly, you need to create a Linked Service for ADF to connect to your Databricks Cluster. You can connect to as many clusters as you want.
Then create a...Read more
IBM watsonx.data has no discussions with answers
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